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profesor instytutu

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Publikacje

2020

1. Głomb, P., and M. Romaszewski, "Anomaly detection in hyperspectral remote sensing images", Hyperspectral Remote Sensing: Theory & Applications: Elsevier, 2020.

2019

2. Cholewa, M., P. Głomb, and M. Romaszewski, "A Spatial-Spectral Disagreement-Based Sample Selection With an Application to Hyperspectral Data Classification", IEEE Geoscience and Remote Sensing Letters, vol. 16, pp. 467-471, March, 2019.
4. Głomb, P., K. Domino, M. Romaszewski, and M. Cholewa, "Band selection with Higher Order Multivariate Cumulants for small target detection in hyperspectral images", PP-RAI'2019, Wrocław, Poland, Wroclaw University of Science and Technology, pp. p. 121, 2019.
5. Grabowski, B., P. Głomb, M. Romaszewski, and M. Ostaszewski, "Unsupervised deep learning approach to hyperspectral anomaly detection", PP-RAI'2019, Wrocław, Poland, Wroclaw University of Science and Technology, 2019.

2018

7. Romaszewski, M., P. Głomb, and M. Cholewa, "Adaptive, Hubness-Aware Nearest Neighbour Classifier with Application to Hyperspectral Data", Computer and Information Sciences: Springer International Publishing, 2018.
8. Grabowski, B., W. Masarczyk, P. Głomb, and A. Mendys, "Automatic pigment identification from hyperspectral data", Journal of Cultural Heritage, vol. 31, pp. 1 - 12, 2018.

2017

9. Cholewa, M., P. Gawron, P. Głomb, and D. Kurzyk, "Quantum hidden Markov models based on transition operation matrices", Quantum Information Processing, vol. 16, pp. 101, 2017.

2016

10. Romaszewski, M., and P. Głomb, "Parameter Estimation for HOSVD-based Approximation of Temporally Coherent Mesh Sequences", Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 2016.
11. Romaszewski, M., P. Głomb, and M. Cholewa, "Semi-supervised hyperspectral classification from a small number of training samples using a co-training approach", ISPRS Journal of Photogrammetry and Remote Sensing, vol. 121, pp. 60 - 76, 2016.
12. Cholewa, M., and P. Głomb, "Two Stage SVM Classification for Hyperspectral Data", Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, 2016.
13. Głomb, P., and M. Cholewa, "Performance of Interest Point Descriptors on Hyperspectral Images", Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, 2016.

2015

14. Domino, K., P. Głomb, and Z. Łaskarzewski, "Classification of LPG clients using the Hurst exponent and the correlation coeficient", Theoretical and Applied Informatics, vol. 27, issue 1, pp. 13–24, 2015.
15. Głomb, P., and M. Cholewa, "Experimental Evaluation of Selected Approaches to Covariance Matrix Regularization", Artificial Intelligence and Soft Computing, vol. 9120: Springer International Publishing, pp. 391-401, 2015.

2014

16. Romaszewski, M., P. Głomb, and P. Gawron, "Natural hand gestures for human identification in a Human-Computer Interface", Image Processing Theory Tools and Applications (IPTA), 2014 4th International Conference on: IEEE, pp. 404–409, 10, 2014.
17. Głomb, P., and A. Sochan, "Surface Mixture Models for the Optimization of Object Boundary Representation", Artificial Intelligence and Soft Computing, Lecture Notes in Computer Science 8467, pp. 703–714, 2014.

2013

18. Cholewa, M., P. Głomb, S. Opozda, M. Romaszewski, A. Sochan, M. Kosiedowski, E. Kuśmierek, A. Bęben, P. Krawiec, and A. Stroiński, "Aplikacje Sieci Świadomej Treści", Inżynieria Internetu przyszłości część 2: Oficyna Wydawnicza PW, 2013.

2012

20. Głomb, P., M. Romaszewski, S. Opozda, and A. Sochan, "Choosing and Modeling the Hand Gesture Database for a Natural User Interface", Gesture and Sign Language in Human-Computer Interaction and Embodied Communication, Lecture Notes in Artificial Intelligence: Springer Berlin Heidelberg, 2012.
22. Blachnik, M., and P. Głomb, "Do we need complex models for gestures? A comparison of data representation and preprocessing methods for hand gesture recognition", Artificial Intelligence and Soft Computing Lecture Notes in Computer Science 7267: Springer Berlin Heidelberg, pp. 477–485, 2012.

2011

23. Cholewa, M., and P. Głomb, "Gesture data modeling and classification based on critical points approximation", Advances in Intelligent and Soft Computing, 2011, Volume 95, Computer Recognition Systems 4,, vol. 95, pp. 365–373, 2011.
24. Gawron, P., P. Głomb, J. Miszczak, and Z. Puchała, "Eigengestures for natural human computer interface", Man-Machine Interactions 2, Berlin / Heidelberg, Springer, pp. 49–56, 2011.
25. Sochan, A., P. Głomb, K. Skabek, M. Romaszewski, and S. Opozda, "Virtual Museum as an Example of 3D Content Distribution in the Architecture of a Future Internet", Computer Networks 2011. Communications in Computer and Information Science 160., pp. 459–464, 2011.

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